دورية أكاديمية
A Bayesian latent class model to estimate the accuracy of pregnancy diagnosis by transrectal ultrasonography and laboratory detection of pregnancy-associated glycoproteins in dairy cows.
| العنوان: | A Bayesian latent class model to estimate the accuracy of pregnancy diagnosis by transrectal ultrasonography and laboratory detection of pregnancy-associated glycoproteins in dairy cows. |
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| المؤلفون: | Fosgate GT; University of Pretoria, Faculty of Veterinary Science, Department of Production Animal Studies, Onderstepoort, 0110, South Africa. Electronic address: geoffrey.fosgate@up.ac.za., Motimele B; University of Pretoria, Faculty of Veterinary Science, Department of Production Animal Studies, Onderstepoort, 0110, South Africa; Agricultural Research Council-Animal Production Institute, Irene 0062, South Africa., Ganswindt A; University of Pretoria, Faculty of Veterinary Science, Endocrine Research Laboratory, Department of Anatomy and Physiology, Onderstepoort 0110, South Africa., Irons PC; University of Pretoria, Faculty of Veterinary Science, Department of Production Animal Studies, Onderstepoort, 0110, South Africa; Murdoch University, College of Veterinary Medicine, School of Veterinary and Life Sciences, Western Australia, 6150, Australia. |
| المصدر: | Preventive veterinary medicine [Prev Vet Med] 2017 Sep 15; Vol. 145, pp. 100-109. Date of Electronic Publication: 2017 Jul 05. |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: Elsevier Scientific Publishing Country of Publication: Netherlands NLM ID: 8217463 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-1716 (Electronic) Linking ISSN: 01675877 NLM ISO Abbreviation: Prev Vet Med Subsets: MEDLINE |
| أسماء مطبوعة: | Publication: Amsterdam : Elsevier Scientific Publishing Original Publication: Amsterdam, Netherlands : Elsevier, [1982- |
| مواضيع طبية MeSH: | Glycoproteins/*analysis , Pregnancy, Animal/*physiology , Ultrasonography/*veterinary, Animals ; Bayes Theorem ; Cattle ; Female ; Insemination, Artificial/veterinary ; Milk/chemistry ; Pregnancy ; Prospective Studies ; South Africa ; Ultrasonography/methods |
| مستخلص: | Accurate diagnosis of pregnancy is an essential component of an effective reproductive management plan for dairy cattle. Indirect methods of pregnancy detection can be performed soon after breeding and offer an advantage over traditional direct methods in not requiring an experienced veterinarian and having potential for automation. The objective of this study was to estimate the sensitivity and specificity of pregnancy-associated glycoprotein (PAG) detection ELISA and transrectal ultrasound (TRUS) in dairy cows of South Africa using a Bayesian latent class approach. Commercial dairy cattle from the five important dairy regions in South Africa were enrolled in a short-term prospective cohort study. Cattle were examined at 28-35days after artificial insemination (AI) and then followed up 14days later. At both sampling times, TRUS was performed to detect pregnancy and commercially available PAG detection ELISAs were performed on collected serum and milk. A total of 1236 cows were sampled and 1006 had complete test information for use in the Bayesian latent class model. The estimated sensitivity (95% probability interval) and specificity for PAG detection serum ELISA were 99.4% (98.5, 99.9) and 97.4% (94.7, 99.2), respectively. The estimated sensitivity and specificity for PAG detection milk ELISA were 99.2% (98.2, 99.8) and 93.4% (89.7, 96.1), respectively. Sensitivity of veterinarian performed TRUS at 28-35days post-AI varied between 77.8% and 90.5% and specificity varied between 94.7% and 99.8%. In summary, indirect detection of pregnancy using PAG ELISA is an accurate method for use in dairy cattle. The method is descriptively more sensitive than veterinarian-performed TRUS and therefore could be an economically viable addition to a reproductive management plan. (Copyright © 2017 Elsevier B.V. All rights reserved.) |
| فهرسة مساهمة: | Keywords: Bayesian; Dairy cattle; Pregnancy; Sensitivity; Specificity |
| المشرفين على المادة: | 0 (Glycoproteins) |
| تواريخ الأحداث: | Date Created: 20170915 Date Completed: 20180402 Latest Revision: 20181202 |
| رمز التحديث: | 20221213 |
| DOI: | 10.1016/j.prevetmed.2017.07.004 |
| PMID: | 28903866 |
| قاعدة البيانات: | MEDLINE |
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